{"id":"W4390532199","doi":"10.15353/joci.v19i1.5583","title":"Community informatics and artificial intelligence","year":2023,"lang":"en","type":"article","venue":"The Journal of Community Informatics","topic":"Big Data and Business Intelligence","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Informatics; Artificial intelligence; Computer science; Data science; Engineering","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.006192893,0.0001702478,0.0002660488,0.0003909573,0.001301476,0.0004257936,0.0016195,0.00007604875,0.00004658854],"category_scores_gemma":[0.0007002117,0.0001125573,0.00006132397,0.001041721,0.0003382697,0.002886796,0.001159584,0.001681764,0.0002952299],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002004211,"about_ca_system_score_gemma":0.00003636544,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003026482,"about_ca_topic_score_gemma":0.00009614001,"domain_scores_codex":[0.9979889,0.0001349308,0.001203519,0.000006078981,0.0004182641,0.0002482819],"domain_scores_gemma":[0.9970974,0.0006768473,0.001078153,0.0006211491,0.0005037636,0.00002266411],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"qualitative","study_design_scores_codex":[0.0004501226,0.0005790418,0.001989096,0.003507083,0.0002850844,0.000002401696,0.3203613,0.01055295,0.0001534727,0.04945064,0.06291992,0.5497489],"study_design_scores_gemma":[0.000208514,0.0001147223,0.004652799,0.0003647508,0.0002181767,0.0001752755,0.8201264,0.03866127,0.0003557244,0.07736099,0.05733767,0.000423772],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9792257,0.00002633552,0.01469143,0.0009875989,0.0003494103,0.0001146104,0.000006169322,0.00006559075,0.004533159],"genre_scores_gemma":[0.9974781,0.0002485717,0.0002483683,0.001758912,0.0002053279,9.051146e-7,0.00002500789,0.00001101055,0.00002380731],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5493251,"threshold_uncertainty_score":0.9999987,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.159085004101757,"score_gpt":0.3266012677298051,"score_spread":0.167516263628048,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}